It is widely recognized that clustering ensemble is fit for any shape and any distribution dataset and that the boosting method provides superior results for classification problems. In the paper, a dual boosting is p...
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It is widely recognized that clustering ensemble is fit for any shape and any distribution dataset and that the boosting method provides superior results for classification problems. In the paper, a dual boosting is proposed for fuzzy clustering ensemble . At each boosting iteration, a new training set is created based on the original datasets' probability which is associated with the previous clustering. According to the dual boosting method, the new training subset contains not only the instances which is hard to cluster in previous stages , but also the instances which is easy to cluster. The final clustering solution is produced by using the clustering based on the co-association matrix. Experiments on both artificial and realworld datasets demonstrate the efficiency of the fuzzy clustering ensemble based on dual boosting in stability and accuracy.
Authorization mechanism is an effective technique of access control. In this paper, we construct a multidimensional authorization space for RSM with the guidance of the methodology of RSM design. This authorization sp...
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The DS-CDMA signal model and the noisy linear independent component analysis (ICA) model are analyzed in this paper. Comparing these models shows that they have the same form. The adaptive minimum mean-square error (M...
The DS-CDMA signal model and the noisy linear independent component analysis (ICA) model are analyzed in this paper. Comparing these models shows that they have the same form. The adaptive minimum mean-square error (MMSE) multiuse detection based on ICA is proposed. It uses the output of adaptive MMSE multi-user detection to initialize the ICA iterations, not only the known spread information of interesting user is used to overcome the uncertainness of ICA, but also the character of statistical independence is used. The simulation results show that the performance is improved obviously.
A novel image content authentication algorithm based on Laplace spectra was proposed. Outstanding feature points are extracted from the original image and a cipher point is inserted. A relational graph is then built, ...
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ISBN:
(纸本)7900719229
A novel image content authentication algorithm based on Laplace spectra was proposed. Outstanding feature points are extracted from the original image and a cipher point is inserted. A relational graph is then built, and the Laplace spectra of the graph are calculated to serve as image features. The Laplace spectra are quantized then embedded into the original image as a watermark. In the authentication step, the Laplace spectra of the authenticating image are calculated and compared with that of the watermark embedded in the authenticating image. If both of the spectra are identical, the image passes the authentication test. Otherwise, the tamper is found. The experimental results show that the proposed authentication algorithm can effectively detect the event and the location when the original image content is tampered viciously.
The multifractal spectrum of protein feature sequences was computed and analyzed with the multifractal. The parameters of multifractal spectra were used to describe hierarchically refined structure of protein feature ...
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ISBN:
(纸本)7900719229
The multifractal spectrum of protein feature sequences was computed and analyzed with the multifractal. The parameters of multifractal spectra were used to describe hierarchically refined structure of protein feature sequences and pop out the singularity of local sequences. And with using quotient space granularity computing theory power gene a of multifractal was chosen wilder. Constructing 2D space, and it presented good efficiency in structure classing, which is favor of predicting protein structure class.
The mechanism of the classical particle swarm optimization and the comparison criterion of different natural computing methods is investigated by introducing the discrepancy and good lattice points in number theory an...
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The mechanism of the classical particle swarm optimization and the comparison criterion of different natural computing methods is investigated by introducing the discrepancy and good lattice points in number theory and proposes a novel optimization method, called good lattice points-based particle swarm optimization algorithm, which intends to produce faster and more accurate convergence because it has a solid theoretical basis and better global search ability, meanwhile the global convergence of the presented algorithm with asymptotic probability one is proved by the property of the optimal lattice. Finally experiment results are very promising to illustrate the outstanding feature of the presented algorithm.
In this article, we propose a (t,n) threshold verifiable multi-secret sharing scheme, in which to reconstruct t secrets needs to solve t simultaneous equations. The analysis results show that our scheme is as easy as ...
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In this article, we propose a (t,n) threshold verifiable multi-secret sharing scheme, in which to reconstruct t secrets needs to solve t simultaneous equations. The analysis results show that our scheme is as easy as Yang's scheme [8] in the secret reconstruction and requires less public values than Chien's [7] and Yang's schemes. Furthermore, the shares in our scheme can be verified their validity with t public values based on ECDLP, and there are two verified forms: one is computationally secure as Feldman 's scheme [12] and other is unconditionally secure as Pedersen's scheme [13]. In addition, for the main computation: a i,1 P 1 + a i,2 P 2 + hellip + a i,t P t in our scheme, we present a new method based on the signed factorial expansion and implement it, the results show that it is more efficient than the current public methods. Thus our scheme is a secure and efficient (t,n) threshold verified multi-secret sharing scheme.
The digital image over the network is inevitably affected by the channel additive noise. However the existing fragile watermarking techniques with recovery are susceptible to random noise. To overcome this problem, th...
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The digital image over the network is inevitably affected by the channel additive noise. However the existing fragile watermarking techniques with recovery are susceptible to random noise. To overcome this problem, this paper presents a chaos-based fragile watermarking scheme with recovery. In the proposed algorithm, the original image is divided into 2times2 blocks. The watermark embedding position of every image block is randomly generated based on chaotic system. These strategies can effectively improve the ability of our algorithm against not only random noise but also the synchronous counterfeiting attack. The experiment demonstrates that the proposed scheme can detect and localize any malicious alterations and can recover a tampered image to an intelligible one even if the tested image is polluted by the random noise.
A novel Pareto-based multi-objective fully-informed particle swarm algorithm (FIPS) is proposed to solve flexible job-shop problems in this paper. Firstly, the population is ranked based on Pareto optimal concept. And...
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A novel Pareto-based multi-objective fully-informed particle swarm algorithm (FIPS) is proposed to solve flexible job-shop problems in this paper. Firstly, the population is ranked based on Pareto optimal concept. And the neighborhood topology used in FIPS is based on the Pareto rank. Secondly, the crowding distance of individuals is computed in the same Pareto level for the secondary rank. Thirdly, addressing the problem of trapping into the local optimal, the mutation operators based on the coding mechanism are introduced into our algorithm. Finally, the performance of the proposed algorithm is demonstrated by applying it to several benchmark instances and comparing the experimental results.
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